1. Introduction to Data Visualization

2. Introduction to ggplot

3. Overview of the Gapminder Dataset

4. Exploration of GDP Per Capita

5. Exploration of Life Expectancy

6. Extention libraries to ggplot2

Figure: Data Science Project Workflow

Source: http://r4ds.had.co.nz/introduction.html

1. ggplot2 is a data visualization package for the statistical programming language R.

2. Created by Hadley Wickham in 2005

3. Implementation of Leland Wilkinson's Grammar of Graphics

4. Easy plotting with qplot function

5. Complex plotting with ggplot function

6. ggplot for python

1. Free and open source

2. Professional quality graphs

3. Literate programming

4. Easy superposition (Multiple Plots in a graph)

5. Multiple themes + ggthemes

6. Large number of extention libraries

More reasons why you should use ggplo2: https://github.com/tidyverse/ggplot2/wiki/Why-use-ggplot2

Sample dataframe from 1704 records of the Gapminder dataset.

Source:
https://cran.r-project.org/web/packages/ggnetwork/vignettes/ggnetwork.html

1. https://github.com/jennybc/ggplot2-tutorial

2. https://medium.com/optima-blog/using-polar-coordinates-for-better-visualization-1d337b6c9dec

3. http://r4ds.had.co.nz

4. http://www.stat.columbia.edu/~tzheng/files/Rcolor.pdf